Goodness-of-fit tests based on Rao's divergence under sparseness assumptions

DOI10.1016/S0096-3003(01)00095-9zbMath1016.62058OpenAlexW1984272737MaRDI QIDQ1855740

María del Carmen Pardo

Publication date: 28 January 2003

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0096-3003(01)00095-9

zbMATH Keywords

efficiencypower functionsparseness assumptions

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Statistical aspects of information-theoretic topics (62B10)

Related Items (3)

Testing stationary distributions of Markov chains based on Rao's divergence ⋮ Improving the accuracy of goodness-of-fit tests based on Rao's divergence with small sample size. ⋮ Goodness-of-fit tests for stationary distributions of Markov chains based on Rao's divergence

Cites Work

• Goodness-of-fit statistics for discrete multivariate data
• Central limit theorems for multinomial sums
• On Burbea-Rao divergence based goodness-of-fit tests for multinomial models
• Divergence statistics: sampling properties and multinomial goodness of fit and divergence tests
• Separable Statistics and Hypothesis Testing. The Case of Small Samples
• On the convexity of some divergence measures based on entropy functions
• Asymptotic distributions of φ‐divergences of hypothetical and observed frequencies on refined partitions
• About distances of discrete distributions satisfying the data processing theorem of information theory
• Asymptotically Optimal Tests for Multinomial Distributions
• Asymptotic normality and efficiency for certain goodness-of-fit tests
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